In recent years, the autonomous mobile robot has found diverse applications such as home/health care system, surveillance system in civil and military applications and exhibition robot. For surveillance tasks such as moving target pursuit or following and patrol in a region using mobile robot, this paper presents a fuzzy Q-learning, as an intelligent control for cost-based navigation, for autonomous learning of suitable behaviors without the supervision or external human command. The Q-learning is used to select the appropriate rule of interval type-2 fuzzy rule base. The initial testing of the intelligent control is demonstrated by simulation as well as experiment of a simple wall-following based patrolling task of autonomous mobile robot.
CITATION STYLE
Lo, C. W., Wu, K. L., Lin, Y. C., & Liu, J. S. (2014). An intelligent control system for mobile robot navigation tasks in surveillance. In Advances in Intelligent Systems and Computing (Vol. 274, pp. 449–462). Springer Verlag. https://doi.org/10.1007/978-3-319-05582-4_39
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